Data underlying the paper "Identifying Algorithmic Decision Subjects' Needs for Meaningful Contestability"

DOI:10.4121/be171486-fe03-45fe-8d8b-22b4c81cd3a2.v2
The DOI displayed above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
DOI: 10.4121/be171486-fe03-45fe-8d8b-22b4c81cd3a2

Datacite citation style

Yurrita Semperena, Mireia; Verma, Himanshu; Balayn, Agathe; Alfrink, Kars; Gadiraju, Ujwal et. al. (2025): Data underlying the paper "Identifying Algorithmic Decision Subjects' Needs for Meaningful Contestability". Version 2. 4TU.ResearchData. dataset. https://doi.org/10.4121/be171486-fe03-45fe-8d8b-22b4c81cd3a2.v2
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite

Dataset

Version 2 - 2025-03-18 (latest)
Version 1 - 2025-02-17

This project characterizes decision subjects' information and procedural needs for meaningful contestability in an algorithmic decision-making process for policy enforcement. We interviewed 21 participants with experience renting their properties out as short-term rentals. We introduced a hypothetical algorithmic system for identifying illegal holiday rentals and informed participants that their property had been identified as an illegal holiday rental. Throughout the interviews we captured their needs to meaningfully contest the algorithmic decision and the decision-making process as a whole. The dataset includes:


  1. The pre-registration of the study
  2. The screening survey
  3. The interview protocol
  4. The prompts used as part of the interviews

History

  • 2025-02-17 first online
  • 2025-03-18 published, posted

Publisher

4TU.ResearchData

Format

.pdf

Organizations

TU Delft, Faculty of Industrial Design Engineering, Department of Human-Centered Design
TU Delft, Faculty of Industrial Design Engineering, Department of Sustainable Design Engineering
TU Delft, Faculty of Electrical Engineering, Mathematics and Computer Science, Department of Software Technology

DATA

Files (9)